Implantable cardiac device have recently become increasingly commonplace in providing cardiac therapies to patients in need of constant monitoring of heart conditions that require immediate treatment. These cardiac devices typically provide a single therapy, or at most a few different therapies, to a patient depending upon a small set of observable parameters regarding the condition of a patient's heart. As a result of the more widespread use of such devices, it is becoming more evident that the operation of these devices need to be customized to provide a more optimal set of therapies to any given patient.
The computational capabilities inherent within implantable devices has increased along with the general increase in computational technology during this same time period. However, performing more complex computations also results in increased power consumption on any given computational platform, including the devices within implantable systems. As a result, many data processing strategies have not been readily utilized in these devices as the computational requirements of such systems has typically been too complex to be realistically utilized.